santhisenan/DeepDefense
DDoS attack detection using BLSTM based RNN
Implements bidirectional LSTM (BLSTM) architecture for packet-level DDoS classification, processing network traffic features extracted from the ISCX 2012 dataset. The model captures temporal attack patterns in both directions through sequential packet analysis, achieving measurable accuracy and loss convergence over 40 training epochs. Designed as a Jupyter notebook workflow for straightforward training and evaluation on labeled network traffic data.
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76
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26
Language
Jupyter Notebook
License
MIT
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Last pushed
May 03, 2020
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